courseraАнализ данных

Forecast Business Metrics: Uncover Value Drivers

Курс от Coursera

Средний≈ 2.6 чАнглийский

О курсе

In this short, practical course, you’ll learn how to use supervised learning to forecast key business metrics and uncover the drivers that shape performance. Through hands-on exercises in Python, you’ll build and tune regression and gradient-boosted models to predict outcomes such as next-quarter EBITDA. Then, you’ll apply explainable AI techniques, including SHAP and feature importance, to translate model outputs into clear, actionable business insights. By the end of the course, you’ll be able to evaluate forecast accuracy, identify which variables truly drive results, and communicate your findings in simple, stakeholder-ready language. Designed for analysts and data professionals, this course helps you connect data science methods to real-world business forecasting and decision-making.

Навыки, которые вы освоите

Model Evaluation Supervised Learning Regression Analysis Forecasting Predictive Modeling Business Metrics Applied Machine Learning Technical Communication Financial Forecasting Model Training Data Storytelling Data-Driven Decision-Making Predictive Analytics Stakeholder Communications Advanced Analytics Performance Analysis Business Analytics Data Science

Программа курса

1 модулей · 16 учебных материалов

01Forecast Business Metrics: Uncover Value Drivers16 материалов

Forecasting with Supervised Learning

Introduction and Why Forecasts Drive Better Business DecisionsВидео What Metrics Would You Forecast in Your Role?DIALOGUE Supervised methods for Business ForecastingЧтение Gradient Boosting vs. Linear Models: Choosing What WorksВидео

Учитесь у экспертов

Professionals in the Industry

ansrsource instructors